The cortical pathway responsible for motion processing is relatively well defined (see e.g. Britten, 2003 for review). However, an understanding of the precise mechanisms involved in encoding the speed of a moving image has proven evasive. A variety of models have been proposed, including labelled line, ratio and Bayesian models (e.g. Priebe & Lisberger, 2004; Smith & Edgar, 1994; Thompson, Brooks, & Hammett, 2006; Hammett, Champion, Thompson, & Morland, 2007; Stocker & Simoncelli, 2006; Langley & Anderson, 2007) but there is still no clear, agreed picture of exactly where in the pathway speed-tuning arises, nor how it is achieved. The location of an unambiguous speed signal is not only of anatomical interest but is likely to constrain models of how the spatio-temporally separable signals generated in the retina are transformed to provide behaviourally relevant cues to speed. Unfortunately previous attempts to determine the locus of speed encoding using both electrophysiological and imaging techniques have yielded inconclusive results.
There is considerable electrophysiological evidence to suggest that the early stages of visual processing are mediated by neurones whose responses are spatio-temporally separable (e.g. Tolhurst & Movshon, 1975; Foster, Gaska, Nagler & Pollen, 1985). Such neurones are tuned for limited ranges of spatial and temporal frequency and thus do not provide an unambiguous code for speed. More recent evidence of the speed tuning of many neurones in MT (e.g. Perrone & Thiele, 2001) and a direct link between their activity and speed perception (e.g. Rudolph & Pasternak, 1999; Liu & Newsome, 2005) raises the possibility that an explicit code for speed may be extracted from early spatially and temporally ...
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... response. The expectation of such a coupling, at least in MT, seems reasonable in light of evidence (Liu & Newsome, 2005) that individual neurons in MT play a direct role in speed perception. Thus examining the effect of a stimulus attribute that is known to affect perceived speed on BOLD responses may render a clearer picture of how and where cortical speed encoding occurs.
Recently, Hammett et al. (2007) have shown that perceived speed is modulated by mean luminance such that low luminance stimuli appear significantly faster at high speeds. Any coupling of the BOLD response to perceived speed should therefore be manifested by systematic differences in areas that encode speed. We have therefore measured the BOLD response to drifting sinusoidal gratings at a range of speeds and at two luminance levels above the scotopic range, in areas from the LGN to MST.
The ultimate goal for a system of visual perception is representing visual scenes. It is generally assumed that this requires an initial ‘break-down’ of complex visual stimuli into some kind of “discrete subunits” (De Valois & De Valois, 1980, p.316) which can then be passed on and further processed by the brain. The task thus arises of identifying these subunits as well as the means by which the visual system interprets and processes sensory input. An approach to visual scene analysis that prevailed for many years was that of individual cortical cells being ‘feature detectors’ with particular response-criteria. Though not self-proclaimed, Hubel and Wiesel’s theory of a hierarchical visual system employs a form of such feature detectors. I will here discuss: the origins of the feature detection theory; Hubel and Wiesel’s hierarchical theory of visual perception; criticism of the hierarchical nature of the theory; an alternative theory of receptive-field cells as spatial frequency detectors; and the possibility of reconciling these two theories with reference to parallel processing.
Hubel and Wiesel’s research surrounding area V1 of the primary visual cortex provided one of the first descriptions of the receptive fields in mammals. By flashing various lines along the receptive field, Hubel and Wiesel were able to classify cortical neurons into two distinct groups; simple and complex (Hubel & Wiesel, 1963). The use of manually mapping the receptive fields with simple dots, lines and edges meant that they not only discovered orientation tuning in single neurons, but also described the columnar organisation of ocular dominance and orientation preferences in the cerebral cortex (Ringach, 2004). Although Hubel and Wiesel’s findings were an extreme advance in our understanding of the visual cortex (Wurtz, 2009), it became apparent that there were cells in the visual system that responded to stimuli far more complicated than orientated lines meaning that the cells in area V1 were much more modifiable than Hubel and Wiesel had suggested. In this essay, Hubel and Wiesel’s classic receptive field shall be discussed along with reasons as to why it can no longer offer us a satisfactory explanation into visual perception. First to be discussed are the specific types of cells which were defined in Hubel and Wiesel’s classic experiment into the striate cortex.
According to Dr. Vilayanur Ramachandran, in his movie “Secrets of the Mind,” our vision system is divided into two parts, one with our eyes, and the other with our brain. He also says that there are two different pathways in which our brain uses to “see.” One of these pathways, he calls the evolutionary new pathway (the more sophisticated pathway) in which our eyes see, then the information is sent to the thalamus, and eventually entering the visual cortex of the brain. This pathway is the conscious part of seeing. The other pathway Dr. Ramachandran says is more prominent, as well as evolutionarily primitive. An iguana uses this system of seeing. In this second pathway, information enters through the eyes, and then is sent to the brain stem, which in turn relays the information to the higher center of the brain. Dr. Ramachandran says that this second system is used to orientate our eyes to look at things, especially movement. Dr. Ramachandran has looked at patients with what is known as blind-sight to form his hypothesis.
Figure 1.2 shows a simple schematic detailing the combination or retinal information and eye velocity estimates to generate a perceived motion direction. This diagram is analogous to figure 1.1, showing the integration of signals from a lower ‘detector’ level, at the eye movement and retinal velocity estimate level, and later at an integrator stage, after which the motions have been transformed into the perceived direction. This diagram also illustrates the focus of chapters 2, 3 and 4. Chapter 2 investigates the motion aftereffect (see adaptation section) which follows simultaneous retinal motion and repetitive smooth pur...
Vision plays a huge role in the lives of non-human primates. Non-human primates have exceptional binocular vision, due to forward-facing eyes with overlapping visual fields (Prescott). This binocular stereoscopic color vision allows primates to see the world in terms of height, width, and depth, also known as three-dimensional vision (Haviland et al. 2010). Highly developed vision allows the later arboreal primates to judge depth, distance, and location when moving at speed from branch to branch (Haviland et al. 2010). This bino...
A prominent phenomenon in the field of visual science is the motion after-effect (MAE) which is believed to provide a way of bringing together current knowledge of neurophysiology with a measurable visual phenomenon. The MAE is described as a visual illusion produced by viewing any number of motion types (i.e. lateral or vertical linear, spiral, radial or rotation). By viewing a moving physical object for a period of time until the eyes is adapted to the motion. When the motion of the object is stopped, but viewing remains focussed on the object, the viewer may report a slower, reversed/negative movement of the now stationary object (Mather et al, 1998).
Objects that are conveyed by the senses are such as “hard,” “red,” “loud,” and the like. Some are combinations of more than one simple idea derived from more than one sensory input. In the case of “fast,” the speed of something can both be derived from seeing motion as well as feeling motion. Objects conveyed by the operations of the mind are such a...
Physicalism is the position that nothing can exceed past what is physically present, and what is physical is all that there can be. This idea is reductive in that it suggests there is no more to the universe than physical matters, including brain processes, sensations, and human consciousness. J.J.C. Smart explains sensations as a means of commentary on a brain process. He believes that, essentially, brain processes and what we report as sensations are essentially the same thing in that one is an account of the other. He writes in “Sensations and Brain Processes” that “…in so far as a sensation statement is a report of something, that something is in fact a brain process. Sensations are nothing over and above brain processes,” (145). Though
Kanske, P., Heissler, J., Schönfelder, S., Forneck, J., & Wessa, M. (2013). Neural correlates of
Other areas of psychophysics determine the difference in sensitivity for different individuals. Some observers have a tendency to respond to certain stimuli in a distinct way, which is known as response bias. In order to sort out the problem of response bias, signal detection theory (which identifies two distinct responses in sensory detection) is used. The way this is done is by administering an initial test to establish the observer’s sensitivity, followed by a second test which establishes if the observer possesses a response bias...
S Coren, L M Ward & J T Enns 2004 Sensation and Perception 6th edn
There are a limited number of ways to discover and understand how the human mind works and reacts to things. One can not sit and directly observe the brain and eye working together (James, Schneider & Rodgers, 1994). The concept behind mental rotation of images tries to do this by measuring reaction times as the angular disparity of an object increases. Thus, demonstrating the time it takes for the eye and brain to make a connection when presented with a stimulus. Though our experiment was solely limited to calculating reaction times to mental rotations of images, Wohlschlager and Wohlschlager (1998) took this concept one step further to see if mental object rotation and manual object rotation shared a common thought process in our brain.
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Schurger, A., Sitt, J. D., & Dehaene, S. (2012). An accumulator model for spontaneous neural activity prior to self-initiated movement. Proceedings of the National Academy of Sciences, 109(42), E2904-E2913. Retrieved March 21, 2014, from http://dx.doi.org/10.1073/pnas.1210467109
Bergmann, K., Schubert, A., Hagemann, D., & Schankin, A. (2015). Age-related differences in the P3 amplitude in change blindness. Psychological Research, 80(4), 660-676. doi:10.1007/s00426-015-0669-6